Traditional search ranking algorithms rely on an inverted index to match keywords extracted from search queries to keywords associated with one or more documents. Inverted indices store a mapping from content, such as keywords, to its location in a database file, or in a document or set of documents. Those documents having keywords that match search query keywords are returned as search results.
Search ranking algorithms have been developed, however, that rely on additional information in documents besides keywords in order to return more contextually-meaningful search results that better match user intent. The requirements of these new algorithms along with the ever-increasing size of Web data can present issues regarding the storage of document information.